Arnout van de Rijt (European University Institute)

Inferring success-breeds-success from longitudinal records

Abstract. Inequality in human success may emerge through endogenous success-breeds-success dynamics but may also originate in pre-existing differences in talent. It is widely recognized that the skew in static frequency distributions of success implied by success-breeds-success is also consistent with a talent model. Studies have turned to longitudinal records of success, seeking to exploit the time dimension for adjudication. Here we show that success histories suffer from a similar identification problem as static distributional evidence. We prove that for any talent model there exists an analogous path-dependent model that generates the same longitudinal predictions, and vice versa. We provide several examples of such shadow models for prominent models. The crucial implication is that longitudinal evidence from observational data previously interpreted to support success-breeds-success equally fits a talent model and vice versa.

Joint with Alexandros Gelastopoulos and Lucas Sage.